DocumentCode :
2651730
Title :
Implementation of Improved Genetic Algorithm in distribution system with feeder reconfiguration to minimize real power losses
Author :
Ravibabu, P. ; Ramya, M.V.S. ; Sandeep, R. ; Karthik, M.V. ; Harsha, S.
Author_Institution :
ACE Eng. Coll., JNTU, Hyderabad, India
Volume :
4
fYear :
2010
fDate :
16-18 April 2010
Abstract :
The topology of an Electrical Distribution System (EDS) can be suitably modified to minimize the real losses. Basically, losses in an EDS arise due to two factors: 1) fault in the network 2) overload in the feeders. The power losses occurring due to overload or uneven load are dealt in this paper. EDS is normally unevenly loaded and hence often need load balancing, which can also be done by reconfiguring the network like changing the status of both sectionalizing and Tie switches. This paper presents a new approach for optimal reconfiguration of a radial Electrical Distribution Network based on the advanced genetic algorithm using improved methods of selection, crossover and fitness function to determine the optimal configuration path. The opened switches are taken into consideration for crossover process. After obtaining number of solutions (off springs) from the combinational analysis, the optimal solution is selected based on the fitness function, i.e., the solution having the minimal power losses. The proposed approach is tested on IEEE 16 bus system.
Keywords :
genetic algorithms; power distribution faults; electrical distribution system; feeder reconfiguration; genetic algorithm; real power losses; Control systems; Educational institutions; Evolution (biology); Evolutionary computation; Genetic algorithms; Genetic engineering; Load management; Power engineering and energy; Switches; Telecommunication control; Distribution Network Reconfiguration (DNRC); Genetic Algorithm (GA); Improved Genetic Algorithm (IGA);
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Engineering and Technology (ICCET), 2010 2nd International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-6347-3
Type :
conf
DOI :
10.1109/ICCET.2010.5485563
Filename :
5485563
Link To Document :
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